This is an internal function which uses a R code to calculate an
 orthogonalization of a matrix. This function is used in the power method
 allowing to compute an eigendecomposition of a symmetric square.

For a data matrix with m rows and n columns (m>=n), the power
method is used to compute, simultaneously, the eigendecomposition
of a square symmetric matrix. This result is used to obtain the
singular value decomposition (SVD) and the principal component
analysis (PCA) results. Compared to the classical SVD method,
the first r singular values can be computed.

Doulaye Dembele

psvd

Eigendecomposition, Singular-Values and the Power Method

mGS function

<dl> <dt>A</dt>
<dd>Matrix in vector form.</dd></dl>

Arguments

Modified Gram-Schmidt orthogonalization of a matrix — mGS

<dl>

 <dt>A</dt>
<dd>Matrix in vector form.</dd>

</dl>

mGS: Modified Gram-Schmidt orthogonalization of a matrix

Description

Usage

Value

Arguments

Examples